Dropping time from datetime <[M8] in Pandas

Question

So I have a 'Date' column in my data frame where the dates have the format like this

0    1998-08-26 04:00:00  

If I only want the Year month and day how do I drop the trivial hour?

Answer 1

The quickest way is to use DatetimeIndex's normalize (you first need to make the column a DatetimeIndex):

In [11]: df = pd.DataFrame({"t": pd.date_range('2014-01-01', periods=5, freq='H')})  In [12]: df Out[12]:                     t 0 2014-01-01 00:00:00 1 2014-01-01 01:00:00 2 2014-01-01 02:00:00 3 2014-01-01 03:00:00 4 2014-01-01 04:00:00  In [13]: pd.DatetimeIndex(df.t).normalize() Out[13]: <class 'pandas.tseries.index.DatetimeIndex'> [2014-01-01, ..., 2014-01-01] Length: 5, Freq: None, Timezone: None  In [14]: df['date'] = pd.DatetimeIndex(df.t).normalize()  In [15]: df Out[15]:                     t       date 0 2014-01-01 00:00:00 2014-01-01 1 2014-01-01 01:00:00 2014-01-01 2 2014-01-01 02:00:00 2014-01-01 3 2014-01-01 03:00:00 2014-01-01 4 2014-01-01 04:00:00 2014-01-01 

DatetimeIndex also has some other useful attributes, e.g. .year, .month, .day.

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From 0.15 they'll be a dt attribute, so you can access this (and other methods) with:

df.t.dt.normalize() # equivalent to pd.DatetimeIndex(df.t).normalize() 

Answer 2

Another option

df['my_date_column'].dt.date 

Would give

0        2019-06-15 1        2019-06-15 2        2019-06-15 3        2019-06-15 4        2019-06-15